Effects of Pro-Oxidants and Antioxidants on the Total Antioxidant Capacity and Lipid Oxidation Products of Milk During Refrigerated Storage

Optimization of Enzyme-Assisted Extraction of Rosemary Essential Oil Using Response Surface Methodology and Its Antioxidant Activity by Activating Nrf2 Signaling Pathway

Rosemary essential oil (REO) is widely recognized as a food flavoring and traditional herb and possesses potential antioxidant activity. However, its low yield rate and unclarified antioxidant mechanism warrant further investigation. In this study, an enzyme pretreatment-assisted extraction method with Box-Behnken design (BBD) and response surface methodology (RSM) models was employed to optimize the main factors of REO, and its antioxidant molecular mechanism under oxidative stress was elucidated in hydrogen peroxide-induced human lung carcinoma (A549) cells. The optimized yield (4.10%) of REO was recorded with the following optimum conditions: enzyme amount 1.60%, enzyme digestion pH 5.0, enzyme digestion temperature 46.50 °C, and enzyme digestion time 1.7 h. Meanwhile, 1.8-cineole (53.48%) and β-pinene (20.23%) exhibited radical scavenging activity higher than that of BHA and BHT. At the cellular level, REO (12.5-50 µg/mL) increased the levels of cell viability, CAT, SOD, and GSH significantly while reducing the contents of ROS, MDA, and GSSG, when compared to H2O2 exposure. Mechanically, REO relieved oxidative stress via activating the Nrf2 signaling pathway and enhancing the protein expression of Nrf2, NQO-1, and HO-1, which was further verified by molecular docking between the main component 1.8-cineole and the Kelch domain of KEAP1. Therefore, REO could be considered as a potent natural antioxidant with a potential strategy in the food and pharmaceutical industries.

Prediction of detailed blood metabolic profile using milk infrared spectra and machine learning methods in dairy cattle

The adoption of preventive management decisions is crucial to dealing with metabolic impairments in dairy cattle. Various serum metabolites are known to be useful indicators of the health status of cows. In this study, we used milk Fourier-transform mid-infrared (FTIR) spectra and various machine learning (ML) algorithms to develop prediction equations for a panel of 29 blood metabolites, including those related to energy metabolism, liver function/hepatic damage, oxidative stress, inflammation/innate immunity, and minerals. For most traits, the data set comprised observations from 1,204 Holstein-Friesian dairy cows belonging to 5 herds. An exception was represented by β-hydroxybutyrate prediction, which contained observations from 2,701 multibreed cows pertaining to 33 herds. The best predictive model was developed using an automatic ML algorithm that tested various methods, including elastic net, distributed random forest, gradient boosting machine, artificial neural network, and stacking ensemble. These ML predictions were compared with partial least squares regression, the most commonly used method for FTIR prediction of blood traits. Performance of each model was evaluated using 2 cross-validation (CV) scenarios: 5-fold random (CV_r) and herd-out (CV_h). We also tested the best model's ability to classify values precisely in the 2 extreme tails, namely, the 25th (Q25) and 75th (Q75) percentiles (true-positive prediction scenario). Compared with partial least squares regression, ML algorithms achieved more accurate performance. Specifically, elastic net increased the R² value from 5% to 75% for CV_r and 2% to 139% for CV_h, whereas the stacking ensemble increased the R² value from 4% to 70% for CV_r and 4% to 150% for CV_h. Considering the best model, with the CV_r scenario, good prediction accuracies were obtained for glucose (R² = 0.81), urea (R² = 0.73), albumin (R² = 0.75), total reactive oxygen metabolites (R² = 0.79), total thiol groups (R² = 0.76), ceruloplasmin (R² = 0.74), total proteins (R² = 0.81), globulins (R² = 0.87), and Na (R² = 0.72). Good prediction accuracy in classifying extreme values was achieved for glucose (Q25 = 70.8%, Q75 = 69.9%), albumin (Q25 = 72.3%), total reactive oxygen metabolites (Q25 = 75.1%, Q75 = 74%), thiol groups (Q75 = 70.4%), total proteins (Q25 = 72.4%, Q75 = 77.2.%), globulins (Q25 = 74.8%, Q75 = 81.5%), and haptoglobin (Q75 = 74.4%). In conclusion, our study shows that FTIR spectra can be used to predict blood metabolites with relatively good accuracy, depending on trait, and are a promising tool for large-scale monitoring.

Evaluation of The Antioxidant Capacity of Food Products: Methods, Applications and Limitations

Assays of total antioxidant capacity (TAC) are popular in the analysis of food products. This review presents the most popular assays of TAC and their limitations, databases of TAC of food products, their application in clinical studies, and the effect of processing on the TAC of food. The importance of sample preparation for TAC assays and striking effects of digestion in the gastrointestinal tract on the TAC of food are discussed. Critical opinions on the validity of food TAC assays are considered. It is concluded that TAC methods can be useful as screening assays for food quality control and as low-cost, high-throughput tools used to discover potential antioxidant sources and follow changes in the content of antioxidants during food processing. However, effects revealed by TAC assays should be followed and explained using more specific methods.

Response Surface Optimization of Solar Drying Conditions and the Effect on the Quality Attributes and Drying Characteristics of Qula Casein

The objective of this study was to investigate the potential application of a mixed-mode solar dryer to Qula dehydration in the Qinghai-Tibet Plateau of China. A three-factor five-level central composite rotatable design (CCD) of the response surface methodology (RSM) was employed to evaluate the influences of drying process variables on quality attributes in terms of lipid oxidation [peroxide (POV) and thiobarbituric acid reactive substance (TBARS)] and Maillard reaction (5-hydroxymethylfurfural, 5-HMF). The impact of drying temperature (30−50 °C), material thickness (5−15 mm), and wind velocity (0.4−1.4 m/s) on the color, POV, TBARS, and 5-HMF of Qula were studied. Optimum operating conditions were found to be a temperature of 43.0 °C, material thickness of 11.0 mm, and wind velocity of 1.0 m/s based on the minimum of POV, TBARS, and 5-HMF. In this condition, the values of POV, TBARS, and 5-HMF were 0.65 meq/kg, 0.516 mg/kg, and 4.586 mg water/L, respectively, which are significantly lower than for drying of Qula by open sun-drying (p < 0.05). Compared with open sun-drying, the drying time of Qula by solar drying was shortened by 61.5%. The results indicate that the mixed-mode solar dryer is a feasibility drying technology for Qula and could effectively improve the quality of products.

In-line near-infrared analysis of milk coupled with machine learning methods for the daily prediction of blood metabolic profile in dairy cattle

Precision livestock farming technologies are used to monitor animal health and welfare parameters continuously and in real time in order to optimize nutrition and productivity and to detect health issues at an early stage. The possibility of predicting blood metabolites from milk samples obtained during routine milking by means of infrared spectroscopy has become increasingly attractive. We developed, for the first time, prediction equations for a set of blood metabolites using diverse machine learning methods and milk near-infrared spectra collected by the AfiLab instrument. Our dataset was obtained from 385 Holstein Friesian dairy cows. Stacking ensemble and multi-layer feedforward artificial neural network outperformed the other machine learning methods tested, with a reduction in the root mean square error of between 3 and 6% in most blood parameters. We obtained moderate correlations (r) between the observed and predicted phenotypes for γ-glutamyl transferase (r = 0.58), alkaline phosphatase (0.54), haptoglobin (0.66), globulins (0.61), total reactive oxygen metabolites (0.60) and thiol groups (0.57). The AfiLab instrument has strong potential but may not yet be ready to predict the metabolic stress of dairy cows in practice. Further research is needed to find out methods that allow an improvement in accuracy of prediction equations.

Effect of Purple Corn Anthocyanin on Antioxidant Activity, Volatile Compound and Sensory Property in Milk During Storage and Light Prevention

The aim of this study was to observe the effect of purple corn anthocyanin on the light-induced antioxidant activity, free radicals, volatile compounds, color parameters, and sensory properties of milk during storage. There were four groups: (1) negative control, no addition of anthocyanins + exposure to fluorescent light (NC); (2) positive control 1, no addition of anthocyanins + protected from fluorescent light (PC1); (3) positive control 2, the addition of 0.3% (w/v) anthocyanins + exposure to fluorescent light (PC2); and (4) the addition of 0.3% anthocyanins + protected from fluorescent light (AC). The results indicated that the concentration of antioxidant activity parameters in the NC group decreased during the entire storage period, whereas antioxidant activity parameters were unchanged except for the glutathione peroxidase (GSH-Px) in the AC group. Moreover, the NC group showed lower levels of 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity and higher levels of superoxide anion and hydrogen peroxide than the other groups after 1 d of storage period. The extent of malondialdehyde accumulation and lipid peroxidation in the control groups were greater than that of the AC group. Twenty-two volatile compounds were determined in milk, which consisted of eight alcohols, three ketones, five aldehydes, two esters, and four hydrocarbons by headspace gas chromatography mass spectrometer analysis. Specifically, individual aldehydes, esters and hydrocarbons in the AC group remained at relatively stable values during storage relative to the other three groups. Stronger positive correlations were detected between several antioxidant activities (superoxide dismutase, GSH-Px) and DPPH scavenging activity as well as total ketones in milk. Adding of anthocyanin did not impact on the color values of L^*, a^* and b^* in light-protected milk during the entire storage period. Some sensory evaluation parameters (flat, garlic/onion/weedy, oxidized-light, oxidized-metal, rancid) in AC group were significantly higher than that of the control group at the end of the period. In conclusion, the current study revealed that the addition of purple corn anthocyanin pigment to light-protected milk had the potential to prevent lipid oxidation, enhance antioxidant activity, maintain volatile compounds and increase the sensory scores.

Does vitamin fortification affect light oxidation in fluid skim milk?

Off-flavors in milk related to light oxidation form due to photoxidation of native riboflavin and tetrapyrroles, resulting in an array of lipid oxidation compounds. Recent work has established that fortification with water-dispersible vitamin A can result in off-flavors in fluid skim milk caused by vitamin A degradation products in the vitamin premix. The objective of this study was to determine the role of vitamin fortification on light oxidation of high temperature, short time pasteurized fluid skim milk. First, the aroma profiles and aroma-active volatile compounds in light-exposed vitamin premixes were determined by exposing the premixes to fluorescent (FL) or light-emitting diode (LED) light at 2,000 lx at 4°C for 0, 2, 4, 8, or 24 h. A trained panel (n = 6) documented aroma profiles of each vitamin premix at each time point. Headspace solid-phase microextraction followed by gas chromatography-olfactometry and gas chromatography-mass spectrometry (GC-MS) were performed to characterize aroma-active compounds in light-exposed vitamin premixes. In the second experiment, commercial vitamin premixes (vitamin A and vitamin D in oil and water matrices) were used to fortify skim milk (vitamin A: 3,000 IU/946 mL; vitamin D: 600 IU/946 mL). Skim milk was pasteurized, homogenized, and packaged in 946-mL high-density polyethylene jugs. Milks were exposed to FL or LED light at 2,000 lx at 4°C for 4, 12, 24, or 48 h. Controls with and without vitamins and light shielding were included. Riboflavin and vitamin A and D degradation were quantified via ultra-high-performance liquid chromatography. A trained panel (n = 8) documented sensory profiles of milks at each time point. Lipid oxidation volatile compounds were quantified via solid-phase microextraction with GC-MS. Vitamin degradation volatile compounds were quantified via solvent-assisted sorptive stir bar extraction with GC-MS. Riboflavin, vitamin A, and vitamin D degradation were consistent with that reported in previous studies. We found no effect of vitamin fortification on development of typical light oxidation-related off-flavors (cardboard and mushroom) or lipid oxidation-related volatiles (hexanal and heptanal). A perfumey/floral flavor was documented in the oil-based vitamin A-fortified milk, suggesting that light exposure affected the off-flavors contributed by water- versus oil-based vitamin fortification. These results show no evidence that vitamin fortification at current levels provides any protection against light oxidation-related off-flavors in fluid milk.

The antioxidant components of milk and their role in processing, ripening, and storage: Functional food

The current rate of population growth is so fast that, to feed this massive population, a 2-fold increase in land is required for the production of quality food. Improved dietary products such as milk and its products with antioxidant properties and functional foods of animal origin have been utilized to prevent chronic diseases. The designer milk contains low fat and less lactose, more protein, modified level of fatty acids, and desired amino acid profiles. The importance of milk and its products is due to the presence of protein, bioactive peptides, conjugated linoleic acid, omega-3 fatty acid, Vitamin D, selenium, and calcium. These constituents are present in milk product, play a key role in the physiological activities in human bodies, and act as anti-inflammatory, anti-tumor, antioxidant, hypocholesterolemic, immune boosting, and antimicrobial activities. Consumer awareness regarding benefits of designer foods such as milk and its products is almost non-existent worldwide and needs to be established to reach the benefits of designer food technologies in the near future. The main objective of this review was to collect data on the antioxidant properties of milk and its constituents which keep milk-derived products safe and preserved.

Antioxidant activity, total phenolics and flavonoids contents: Should we ban in vitro screening methods?

As many studies are exploring the association between ingestion of bioactive compounds and decreased risk of non-communicable diseases, the scientific community continues to show considerable interest in these compounds. In addition, as many non-nutrients with putative health benefits are reducing agents, hydrogen donors, singlet oxygen quenchers or metal chelators, measurement of antioxidant activity using in vitro assays has become very popular over recent decades. Measuring concentrations of total phenolics, flavonoids, and other compound (sub)classes using UV/Vis spectrophotometry offers a rapid chemical index, but chromatographic techniques are necessary to establish structure-activity. For bioactive purposes, in vivo models are required or, at the very least, methods that employ distinct mechanisms of action (i.e., single electron transfer, transition metal chelating ability, and hydrogen atom transfer). In this regard, better understanding and application of in vitro screening methods should help design of future research studies on 'bioactive compounds'.